A method for studying the influence of blade fouling on the performance of a multistage axial flow compressor

Abstract

The application provides a method for researching the influence of blade fouling on the performance of a multistage axial flow compressor, and relates to the technical field of compressors, and the method comprises the following steps: constructing a fluid domain model and performing grid division on the established initial multistage axial flow compressor model; determining inlet boundary conditions, outlet boundary conditions and related particle properties of particles in order to perform numerical solution on the fluid domain according to the operating conditions of the multistage axial flow compressor, obtaining an initial continuous phase space flow field solution in a cascade channel and an initial migration and deposition distribution rule of particles, thereby obtaining the fouling thickness distribution on the surfaces of blades at each stage after a target simulation operating time, and obtaining a target multistage axial flow compressor fouling model after fouling simulation through a dynamic grid deformation mode; and the influence of blade fouling on the operating performance of the multistage axial flow compressor is analyzed. The method improves the accuracy of numerical simulation results and significantly improves the accuracy and reliability of research.

Description

Technical Field

[0001] This application relates to the field of compressor technology, and in particular to a method for studying the effect of blade fouling on the performance of a multi-stage axial compressor. Background Technology

[0002] For heavy-duty gas turbine generator sets, the multi-stage axial compressor is an indispensable and crucial component. However, during actual operation, due to changes in operating conditions, compressor blades can experience a series of failure modes such as corrosion, wear, and fouling, leading to a severe degradation in the performance of the multi-stage axial compressor and thus affecting the unit's efficiency and economy. Studies have shown that blade fouling is one of the important factors leading to compressor performance degradation, and compressor fouling can reduce the output power of the entire gas turbine unit by nearly 20%.

[0003] Although multi-stage filtration systems are installed at the compressor inlet, fine particles (below 2μm) from the atmosphere can still pass through these systems and enter the compressor. Furthermore, multi-stage axial compressors have high flow capacity and draw in large volumes of air; therefore, even if the particulate matter concentration in the operating environment is low, a significant amount of particulate matter will still enter the compressor along with the intake air. These particles adhere to the compressor blade surfaces, increasing surface roughness and altering the blade geometry. This reduces the effective flow area of ​​the channels, lowers the compressor's aerodynamic efficiency and flow capacity, and severely degrades its performance, ultimately affecting the overall performance of the gas turbine. Therefore, research on the impact of blade fouling on the operating performance of multi-stage axial compressors has significant guiding significance and value for engineering practice.

[0004] Existing methods for studying the impact of fouling on compressor performance mainly involve simulating the change in compressor blade surface roughness caused by fouling by providing a certain equivalent gravel roughness on the blade surface, and then studying the impact of fouling on compressor performance. However, the given equivalent gravel roughness is uniformly distributed along the blade surface, which differs significantly from the actual condition of compressor blades after fouling. This leads to discrepancies between the subsequent numerical study results and the actual compressor performance after fouling. Summary of the Invention

[0005] This application aims to at least partially address one of the technical problems in the related art.

[0006] The first aspect of this application proposes a method for studying the influence of blade fouling on the performance of a multi-stage axial compressor, comprising: S1, performing three-dimensional mapping of the multi-stage axial compressor to be studied, and establishing an initial multi-stage axial compressor model corresponding to the multi-stage axial compressor based on the point cloud data obtained from the three-dimensional mapping;

[0007] S2, Constructing the fluid domain model for the initial multi-stage axial compressor model;

[0008] S3 performs mesh partitioning of the fluid domain for each stage of the moving blades, stationary blades, and the flow channels around the blades in a multi-stage axial compressor.

[0009] S4. Based on the actual operating conditions of the multi-stage axial compressor in production, determine the inlet boundary conditions, outlet boundary conditions, and particulate matter properties of the initial multi-stage axial compressor model under operating conditions.

[0010] S5. Based on the inlet boundary conditions, outlet boundary conditions, and operating conditions, numerical solutions are performed on the fluid domain to obtain the initial continuous phase space flow field solution within the blade passage of the multi-stage axial compressor.

[0011] S6. Based on the particulate matter properties and the initial continuous phase space flow field solution, the discrete term particulate matter is solved to obtain the initial migration and deposition distribution law of particulate matter in the blade passage of a multi-stage axial compressor.

[0012] S7. Based on the initial migration and deposition distribution of particles in the blade channel, the fouling thickness distribution on the surface of each stage blade of the multi-stage axial compressor after the target simulation running time is obtained. Based on the fouling thickness distribution on the surface of each stage blade, the fouling model of the target multi-stage axial compressor after the deposition of particles after the target simulation running time is obtained by dynamic mesh deformation.

[0013] S8 takes the fouling model of a target multi-stage axial compressor as the research object, and numerically solves the fluid domain based on the inlet boundary conditions, outlet boundary conditions and operating conditions to obtain the target continuous phase space flow field solution in the blade passage of the multi-stage axial compressor after fouling simulation.

[0014] S9. By comparing the initial continuous phase space flow field solution in the blade cascade passage of the multi-stage axial compressor with the target continuous phase space flow field solution in the blade cascade passage of the multi-stage axial compressor after fouling simulation, the influence of blade fouling on the operating performance of the multi-stage axial compressor is analyzed.

[0015] According to one embodiment of this application, based on the initial migration and deposition distribution patterns of particles within the blade cascade passage, the fouling thickness distribution on the surface of each stage blade of a multi-stage axial compressor after a target simulation duration is obtained. Based on the fouling thickness distribution on the surface of each stage blade, a fouling model of the target multi-stage axial compressor after particle deposition for the target simulation duration is obtained through dynamic mesh deformation. This includes: dividing the target simulation duration into N sub-simulation durations; obtaining the fouling thickness distribution on the surface of each stage blade of the multi-stage axial compressor after the first sub-simulation duration based on the initial migration and deposition distribution patterns of particles within the blade cascade passage; and obtaining a fouling model of the target multi-stage axial compressor after particle deposition for the target simulation duration through dynamic mesh deformation. A fouling model of the first multi-stage axial compressor was obtained by dynamic mesh deformation after particulate matter deposition for the first sub-simulation duration. The fouling model of the first multi-stage axial compressor was simulated under particulate matter conditions. Based on the inlet and outlet boundary conditions and operating conditions, the fluid domain was numerically solved to obtain the first continuous phase space flow field solution within the multi-stage axial compressor blade passage after the first sub-simulation duration. Based on the particulate matter properties and the first continuous phase space flow field solution, the discrete particulate matter term was solved to obtain the first migration and deposition distribution law of particulate matter within the multi-stage axial compressor blade passage after the first sub-simulation duration. Subsequently, the i-th sub-simulation duration Δt was obtained each time. i Subsequently, when modeling the fouling of a multi-stage axial compressor, the fouling model obtained after the (i-1)th sub-simulation duration is taken as the research object, and the fouling of this research object at the i-th sub-simulation duration Δt is calculated. i The subsequent obtained continuous phase space flow field solution and particle migration and deposition distribution law corresponding to the multi-stage axial compressor fouling model, combined with the i-th sub-simulation duration Δt i The migration and deposition distribution patterns of particulate matter in the fouling model of an internal multi-stage axial compressor are obtained, and the duration Δt of the i-th sub-simulation is obtained. i Then, the fouling thickness distribution on the blade surfaces of each stage of the multi-stage axial compressor is obtained. Based on the fouling thickness distribution on the blade surfaces of each stage, a fouling model of the multi-stage axial compressor after particulate matter deposition for the i-th sub-simulation duration is obtained through dynamic mesh deformation. The above steps of obtaining the multi-stage axial compressor fouling model corresponding to the i-th sub-simulation duration are repeated until the N-th sub-simulation duration Δt is obtained. N The subsequent target is a fouling model for a multi-stage axial compressor.

[0016] According to one embodiment of this application, a three-dimensional mapping of the multi-stage axial compressor to be studied is performed, and an initial multi-stage axial compressor model corresponding to the multi-stage axial compressor is established based on the point cloud data obtained from the three-dimensional mapping. The process includes: performing a three-dimensional mapping of the multi-stage axial compressor to be studied and obtaining point cloud data obtained from the three-dimensional mapping; performing three-dimensional alignment of the point cloud data and constructing blade profiles through point cloud data in different blade height sections; and then obtaining an initial multi-stage axial compressor model through the spatial superposition of the blade profiles.

[0017] According to one embodiment of this application, when constructing a fluid domain model for an initial multi-stage axial compressor model, a particle injection inlet fluid domain of a preset length needs to be constructed in front of the inlet section of the initial multi-stage axial compressor model.

[0018] According to one embodiment of this application, meshing of the fluid domain includes: local mesh control of the surface mesh size of each blade surface of the initial multi-stage axial compressor model to ensure that the surface mesh size of each blade surface is within a preset error range; and local control of the surface mesh size of the fluid domain in the particle injection inlet section to ensure that the surface mesh size of the particle injection inlet surface is within a preset error range.

[0019] According to one embodiment of this application, when performing mesh generation of the fluid domain, the boundary layer mesh is not performed on the fluid domain of the particle injection inlet section.

[0020] According to one embodiment of this application, when numerically solving the fluid domain, the gas is regarded as a continuous phase and the particulate matter as a discrete phase. The solution of the continuous phase spatial flow field is solved using the Euler method, and the solution of the discrete particulate matter is solved using the Lagrange method to solve the particle trajectory.

[0021] According to one embodiment of this application, after obtaining the solution of the continuous phase space flow field in the blade passage of a multi-stage axial compressor each time, the discrete phase particles are solved by the accelerated deposition method.

[0022] According to one embodiment of this application, when the target simulation runtime is divided into N sub-simulation runtimes, the target simulation runtime is evenly distributed to obtain N sub-simulation runtimes.

[0023] According to one embodiment of this application, when analyzing the impact of blade fouling on the operating performance of a multi-stage axial compressor, the compressor's total isentropic efficiency, total pressure ratio, total temperature ratio, and mass flow rate are analyzed.

[0024] This application achieves at least the following beneficial effects: It solves the continuous phase space flow field within the blade cascade passage of a multi-stage axial compressor to obtain the migration and deposition distribution patterns of particles within the cascade passage. Subsequently, it simulates the changes in blade geometry caused by fouling by dynamically deforming each mesh element based on the fouling thickness distribution on the blade surface. Using this method, the deposition distribution characteristics of particles on the blade surface of a multi-stage axial compressor can be obtained, and the non-uniformity of fouling on the blade surface can be simulated through dynamic mesh deformation. This makes the final fouled multi-stage axial compressor model more consistent with the actual fouled multi-stage axial compressor, improving the accuracy of subsequent numerical simulation results and significantly enhancing the accuracy and reliability of the research. Attached Figure Description

[0025] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0026] Figure 1 This is a schematic diagram of an exemplary embodiment of a method for studying the effect of blade fouling on the performance of a multi-stage axial compressor, as shown in this application.

[0027] Figure 2 This is a schematic diagram illustrating dynamic mesh deformation of the mesh elements on the blade surface as shown in this application. Detailed Implementation

[0028] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0029] Figure 1 This is a schematic diagram of an exemplary embodiment of a method for studying the effect of blade fouling on the performance of a multi-stage axial compressor, as shown in this application. Figure 1 As shown, the method for studying the impact of blade fouling on the performance of a multi-stage axial compressor includes the following steps:

[0030] S101, perform three-dimensional mapping of the multi-stage axial compressor to be studied, and establish an initial multi-stage axial compressor model corresponding to the multi-stage axial compressor based on the point cloud data obtained from the three-dimensional mapping.

[0031] The multi-stage axial compressor under study was subjected to 3D mapping to obtain point cloud data. The point cloud data was then 3D aligned, and blade profiles were constructed using point cloud data at different blade height sections. Subsequently, an initial multi-stage axial compressor model was obtained through the spatial inverse reconstruction and stacking of the blade profiles.

[0032] It is easy to understand that this application requires particulate matter fouling simulation of a multi-stage axial compressor. The initial multi-stage axial compressor model mentioned here refers to the original multi-stage axial compressor model without fouling.

[0033] S102, Construct the fluid domain model for the initial multi-stage axial compressor model.

[0034] Based on the initial multi-stage axial compressor model, periodic interfaces between each row of blades are created. For a certain row of blades, the angle between its two periodic flow channel surfaces is 360° / m. i , where m i This refers to the number of blades in each row.

[0035] After creating the single-channel fluid domain for each row of blades, it is also necessary to construct the inlet extension fluid domain and the outlet extension fluid domain at the blade ends of the first and last stages. At the same time, in order to ensure uniform particle injection, a particle injection inlet fluid domain of a preset length needs to be constructed in front of the inlet section of the initial multi-stage axial compressor model.

[0036] S103 performs mesh partitioning of the fluid domain for each stage of the moving blades, stationary blades, and the flow channels surrounding the blades of a multi-stage axial compressor.

[0037] When performing mesh generation in the fluid domain, in order to ensure that the dynamic mesh deformation based on the fouling thickness on the compressor blade surface is not affected by the blade surface mesh elements, the surface mesh size of each blade surface in the initial multi-stage axial compressor model is locally controlled to ensure that the surface mesh size of each blade surface is within the preset error range, which can also be understood as ensuring that the surface mesh size of each blade surface is basically consistent.

[0038] No boundary layer mesh is applied to the fluid domain at the particle inlet. Instead, the surface mesh size is locally controlled to ensure that the surface mesh size at the particle inlet is within a preset error range. This can also be understood as ensuring that the surface mesh size at the particle inlet is basically consistent, so that the particles are uniformly incident from the inlet.

[0039] S104. Based on the actual operating conditions of the multi-stage axial compressor in production, determine the inlet boundary conditions, outlet boundary conditions, and particulate matter properties of the initial multi-stage axial compressor model under operating conditions.

[0040] Among them, the import boundary conditions and export boundary conditions include the compressor inlet total temperature, inlet total pressure and outlet back pressure conditions.

[0041] Among them, the properties of particulate matter include particulate matter type, particulate matter density, and particulate matter thermal conductivity.

[0042] S105, based on the inlet boundary conditions, outlet boundary conditions and operating conditions, numerically solves the fluid domain to obtain the initial continuous phase space flow field solution in the blade passage of the multi-stage axial compressor.

[0043] When numerically solving the spatial flow field and the trajectory of particulate matter in the blade passage of a multi-stage axial compressor, the Euler-Lagrange method is used. Specifically, the gas is regarded as a continuous phase and the particulate matter as a discrete phase. The Euler method is used to solve the solution of the continuous phase spatial flow field, and the Lagrange method is used to solve the particle trajectory for the discrete particulate matter.

[0044] In this application, based on the inlet boundary conditions, outlet boundary conditions, and operating conditions, the Euler method is used to numerically solve the continuous phase space flow field in the compressor blade passage, and the initial continuous phase space flow field solution in the multi-stage axial compressor blade passage is obtained. The initial continuous phase space flow field solution is denoted as ψ0.

[0045] It is not difficult to understand that the initial continuous phase space flow field solution refers to the continuous phase space flow field solution corresponding to the initial multi-stage axial compressor model.

[0046] S106, based on the particulate matter properties and the initial continuous phase space flow field solution, solve the discrete term particulate matter to obtain the initial migration and deposition distribution law of particulate matter in the blade passage of a multi-stage axial compressor.

[0047] Based on the determined properties of the particulate matter, such as particle density, particle size, thermal conductivity, inlet velocity, inlet temperature, and inlet concentration, the Lagrangian method is used to numerically solve for the particle trajectory, obtaining the deposition rate of particles on the surface of each row of blades in a multi-stage axial compressor. The particle density and thermal conductivity are determined according to the particle type, while the inlet velocity and temperature of the particles are consistent with those of the mainstream fluid. Considering the filtering effect of the compressor inlet filter, the particle size is set to 0.1 μm–10 μm.

[0048] Optionally, in order to shorten the numerical solution time, this application uses the accelerated deposition method to solve for discrete phase particles, that is, the particle concentration used in the simulation is set to n times the particle concentration of the multi-stage axial compressor under actual operating conditions.

[0049] S107. Based on the initial migration and deposition distribution of particles in the blade channel, the fouling thickness distribution of each stage of the multi-stage axial compressor blade surface after the target simulation running time is obtained. Based on the fouling thickness distribution of each stage of the blade surface, the fouling model of the target multi-stage axial compressor after the deposition of particles after the target simulation running time is obtained by dynamic mesh deformation.

[0050] In this application, since the accelerated deposition method is used, the target simulated runtime can be set as the ratio of the actual runtime of the multi-stage axial compressor in a particulate environment during production activities to n.

[0051] As an feasible approach, fouling simulation is performed directly on the initial multi-stage axial compressor model for an uninterrupted target simulation duration. This obtains the fouling thickness distribution on the blade surfaces of each stage of the multi-stage axial compressor after the target simulation duration. Based on the fouling thickness distribution on the blade surfaces of each stage, the displacement of each grid element node is performed, simulating the change in compressor blade surface shape caused by fouling after the target simulation duration. This yields a fouling model of the target multi-stage axial compressor after particulate matter has been deposited for the target simulation duration.

[0052] As another feasible approach, the target simulation runtime is divided into N sub-simulation runtimes, denoted as Δt1, Δt2, ..., Δt. i …Δt N .in:

[0053] Δt total =Δt1+Δt2+…+Δt i +…+Δt N =Δt real / n

[0054] Where, Δt total This refers to the target simulation runtime, Δt. real The actual operating time of the compressor is denoted as n, where n is the ratio of the particulate matter concentration set during numerical solution to the actual particulate matter concentration in the environment.

[0055] Based on the initial migration and deposition distribution of particles in the blade passage, the fouling thickness distribution on the blade surfaces of each stage of the multi-stage axial compressor after the first sub-simulation duration Δt1 is obtained. Based on the fouling thickness distribution on the blade surfaces of each stage, the fouling model of the first multi-stage axial compressor after the deposition of particles after the first sub-simulation duration Δt1 is obtained by dynamic mesh deformation.

[0056] The first multi-stage axial compressor model was simulated for fouling under particulate matter conditions. Based on the inlet boundary conditions, outlet boundary conditions, and operating conditions, the fluid domain was numerically solved to obtain the first continuous phase space flow field solution ψ1 in the blade passage of the multi-stage axial compressor after the first sub-simulation duration.

[0057] Based on the particulate matter properties and the first continuous phase space flow field solution ψ1, the discrete term particulate matter is solved to obtain the first migration and deposition distribution law of particulate matter in the multi-stage axial compressor blade passage after the first sub-simulation duration.

[0058] In the following each time, the duration Δt of the i-th sub-simulation is obtained. i Subsequently, when modeling the fouling of a multi-stage axial compressor, the fouling model obtained after the (i-1)th sub-simulation duration is taken as the research object, and the fouling of this research object at the i-th sub-simulation duration Δt is calculated. i The subsequent obtained continuous phase space flow field solution and particle migration and deposition distribution law corresponding to the multi-stage axial compressor fouling model, combined with the i-th sub-simulation duration Δt i The migration and deposition distribution patterns of particulate matter in the fouling model of an internal multi-stage axial compressor are obtained, and the duration Δt of the i-th sub-simulation is obtained. i Then, the fouling thickness distribution on the blade surfaces of each stage of the multi-stage axial compressor is obtained. Based on the fouling thickness distribution on the blade surfaces of each stage, a fouling model of the multi-stage axial compressor after particulate matter deposition for the i-th sub-simulation duration is obtained through dynamic mesh deformation. The above steps of obtaining the multi-stage axial compressor fouling model corresponding to the i-th sub-simulation duration are repeated until the N-th sub-simulation duration Δt is obtained. N The subsequent target is a fouling model for a multi-stage axial compressor.

[0059] Optionally, when dividing the target simulation runtime into N sub-simulation runtimes, the target simulation runtime is evenly distributed to obtain N sub-simulation runtimes, that is, Δt1=Δt2=……=Δt N Furthermore, to ensure a more accurate final dirt accumulation model, N is set to a positive integer greater than 10.

[0060] Figure 2 This application illustrates a schematic diagram of dynamic mesh deformation of the mesh elements on the blade surface, as shown in the diagram. Figure 2 As shown, for the two feasible methods described above, the displacement distance of the mesh element node is the thickness of the deposit within this mesh element, and the displacement direction is the surface normal direction of this mesh element, i.e.

[0061]

[0062] Where m i Δt represents the deposition rate of particles within the grid cell. i Where ρ is the deposition time, F is the particle density, and F is the deposition time. i f is the area of ​​the grid cell. ni N is the surface normal vector of the mesh element, L is the nodal displacement distance, i.e., the fouling thickness of the mesh element. i ′(x′,y′,z′) refers to node N i The node obtained after the (x,y,z) displacement.

[0063] S108 takes the fouling model of a target multi-stage axial compressor as the research object. Based on the inlet boundary conditions, outlet boundary conditions and operating conditions, the fluid domain is numerically solved to obtain the target continuous phase space flow field solution in the blade passage of the multi-stage axial compressor after fouling simulation.

[0064] Taking a fouling model of a multi-stage axial compressor as the research object, the fluid domain is numerically solved based on inlet boundary conditions, outlet boundary conditions, and operating conditions. The target continuous phase space flow field solution within the multi-stage axial compressor blade passage after fouling simulation is obtained, and the final target continuous phase space flow field solution is denoted as ψ. N .

[0065] S109. By comparing the initial continuous phase space flow field solution in the blade cascade passage of the multi-stage axial compressor with the target continuous phase space flow field solution in the blade cascade passage of the multi-stage axial compressor after fouling simulation, the influence of blade fouling on the operating performance of the multi-stage axial compressor is analyzed.

[0066] Compare the final calculated particle deposition Δt total Solution of the target continuous phase space flow field ψ in the blade passage of a multi-stage axial compressor after prolonged fouling N The impact of blade fouling on the operating performance of a multi-stage axial compressor is analyzed by solving the initial continuous phase space flow field ψ0 before fouling. The parameters that need to be analyzed when evaluating the performance of the multi-stage axial compressor include: compressor total-to-total isentropic efficiency, total pressure ratio, total temperature ratio, and mass flow rate.

[0067] This application achieves at least the following beneficial effects:

[0068] 1. This application utilizes three-dimensional mapping of a multi-stage axial compressor to obtain a three-dimensional point cloud model of the compressor and perform reverse reconstruction of the model. This three-dimensional mapping method allows for reverse reconstruction of a specific model of a multi-stage axial compressor, obtaining a prototype model of the multi-stage axial compressor before fouling, facilitating research on the impact of fouling on the performance of specific models of multi-stage axial compressors.

[0069] 2. In constructing the geometric model of the multi-stage axial compressor, this application adds a particle injection inlet section before the inlet section. The particle injection inlet section does not perform boundary layer meshing and the mesh size of the particle injection inlet surface is locally controlled to ensure that the mesh size of the particle injection inlet surface is basically consistent, so that the particles are uniformly injected from the inlet surface, which meets the condition of uniform particle distribution under the actual operating environment of the compressor.

[0070] 3. In this application, when dividing the fluid domain of a multi-stage axial compressor into grids, the surface grid size of the blades is locally controlled to ensure that the surface grid size of each row of blades is basically consistent, so that the dynamic grid deformation is not affected by the grid unit size when it is performed according to the fouling thickness of each grid unit on the blade surface.

[0071] 4. In this application, when numerically solving the migration and deposition distribution patterns of particulate matter within the blade passage of a multi-stage axial compressor, the inlet concentration of the incident particulate matter is considered to be n times the actual particulate matter concentration under the actual compressor operating environment. Using the accelerated deposition method can significantly shorten the numerical simulation time and substantially improve the economy and efficiency of the numerical study.

[0072] 5. In studying the impact of blade fouling on the performance of a multi-stage axial compressor, this application uses the Eulerian-Lagrange method to solve for the continuous phase space flow field within the blade cascade passage of the multi-stage axial compressor, thereby obtaining the migration and deposition distribution patterns of particles within the cascade passage. Subsequently, dynamic mesh deformation is used to dynamically deform each mesh element according to the fouling thickness distribution on the blade surface, simulating the changes in blade geometry caused by fouling. This method allows for the acquisition of the particle deposition distribution characteristics on the blade surface of a multi-stage axial compressor and the non-uniform simulation of fouling on the blade surface through dynamic mesh deformation. This makes the final multi-stage axial compressor model after fouling more consistent with the actual multi-stage axial compressor after fouling, improving the accuracy of subsequent numerical simulation results.

[0073] 6. In studying the impact of fouling on the performance of a multi-stage axial compressor, this application considers the coupling relationship between fouling in the blade passages of the multi-stage axial compressor and the spatial flow field. The entire solution process is divided into several deposition time periods. The fouling model of the multi-stage axial compressor obtained after the previous deposition time period serves as the basis for solving the spatial flow field, particle trajectory, and dynamic mesh deformation in the next stage. This makes the spatial flow field in the blade passages of the multi-stage axial compressor after fouling more consistent with the actual situation of the multi-stage axial compressor after fouling, significantly improving the accuracy and reliability of the study.

[0074] In the description of this application, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential", etc., indicating the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application.

[0075] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, "multiple" means two or more, unless otherwise explicitly specified.

[0076] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0077] Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of this application.

Claims

1. A method of investigating the effect of blade fouling on the performance of a multistage axial compressor, characterised in that, include: S1. Perform three-dimensional mapping of the multi-stage axial compressor to be studied, and establish an initial multi-stage axial compressor model corresponding to the multi-stage axial compressor based on the point cloud data obtained from the three-dimensional mapping. S2, Construct a fluid domain model for the initial multi-stage axial compressor model; S3, For each stage of the multi-stage axial compressor, the moving blades, stationary blades, and the flow channels around the blades are meshed into a fluid domain; S4. Based on the operating conditions of the multi-stage axial compressor in actual production, determine the inlet boundary conditions, outlet boundary conditions, and particulate matter properties of the initial multi-stage axial compressor model under operating conditions. S5. Based on the inlet boundary conditions, outlet boundary conditions, and operating conditions, numerical solutions are performed on the fluid domain to obtain the initial continuous phase space flow field solution within the multi-stage axial compressor blade passage. S6. Based on the particulate matter properties and the initial continuous phase space flow field solution, solve for the discrete particulate matter to obtain the initial migration and deposition distribution law of particulate matter in the multi-stage axial compressor blade passage. S7. Based on the initial migration and deposition distribution law of particles in the blade channel, obtain the fouling thickness distribution on the surface of each stage blade of the multi-stage axial compressor after the target simulation running time, and obtain the fouling model of the target multi-stage axial compressor after the particles have been deposited by dynamic mesh deformation based on the fouling thickness distribution on the surface of each stage blade. S8. Taking the target multi-stage axial compressor fouling model as the research object, the fluid domain is numerically solved based on the inlet boundary conditions, outlet boundary conditions and operating conditions to obtain the target continuous phase space flow field solution in the multi-stage axial compressor blade passage after fouling simulation. S9. By comparing the initial continuous phase space flow field solution in the blade cascade passage of the multi-stage axial compressor with the target continuous phase space flow field solution in the blade cascade passage of the multi-stage axial compressor after fouling simulation, the influence of blade fouling on the operating performance of the multi-stage axial compressor is analyzed.

2. The method of claim 1, wherein, In step S7, based on the initial migration and deposition distribution patterns of particles within the blade passage, the fouling thickness distribution on the surfaces of each stage blade of the multi-stage axial compressor after the target simulation runtime is obtained. Based on this fouling thickness distribution, a fouling model of the target multi-stage axial compressor after particle deposition for the target simulation runtime is obtained through dynamic mesh deformation. This model includes: S71, the target simulation runtime is divided into N sub-simulation runtimes. Based on the initial migration and deposition distribution of particles in the blade channel, the fouling thickness distribution on the surface of each stage blade of the multi-stage axial compressor is obtained after the first sub-simulation runtime. Based on the fouling thickness distribution on the surface of each stage blade, the fouling model of the first multi-stage axial compressor after the first sub-simulation runtime is obtained by dynamic mesh deformation. S72, simulate the fouling operation of the first multi-stage axial compressor fouling model in a particulate environment, and numerically solve the fluid domain according to the inlet boundary conditions, outlet boundary conditions and operating conditions to obtain the first continuous phase space flow field solution in the multi-stage axial compressor blade passage after the first sub-simulation duration. S73, based on the particulate matter properties and the first continuous phase space flow field solution, the discrete term particulate matter is solved to obtain the first migration and deposition distribution law of particulate matter in the multi-stage axial compressor blade passage after the first sub-simulation duration. S74, in each subsequent acquisition of the i-th sub-simulation duration When modeling the fouling of a multi-stage axial compressor, the fouling model obtained after the (i-1)th sub-simulation duration is taken as the research object, and the fouling of this research object at the i-th sub-simulation duration is calculated. The subsequent obtained continuous phase space flow field solution and particle migration and deposition distribution patterns of the multi-stage axial compressor fouling model, combined with the i-th sub-simulation duration, are used to further analyze these findings. The migration and deposition distribution patterns of particulate matter in the fouling model of an internal multi-stage axial compressor are obtained, and the duration of the i-th sub-simulation is determined. Then, the fouling thickness distribution on the surface of each stage blade of the multi-stage axial compressor was obtained, and based on the fouling thickness distribution on the surface of each stage blade, a fouling model of the multi-stage axial compressor after particulate matter has been deposited for the i-th sub-simulation duration was obtained by dynamic mesh deformation. S75, Repeat step S74 above until the Nth sub-simulation duration is obtained. The subsequent target is a fouling model for a multi-stage axial compressor.

3. The method according to claim 1 or 2, characterized in that, The process involves performing three-dimensional mapping of the multi-stage axial compressor under study, and establishing an initial multi-stage axial compressor model based on the point cloud data obtained from the three-dimensional mapping, including: Three-dimensional mapping was performed on the multi-stage axial flow compressor to be studied, and point cloud data obtained from the three-dimensional mapping was acquired. The point cloud data is 3D aligned, and the blade profile is constructed using the point cloud data in different blade height sections. Then, the initial multi-stage axial compressor model is obtained by spatially superimposing the blade profiles.

4. The method according to claim 3, characterized in that, When constructing the fluid domain model of the initial multi-stage axial compressor model, a particle injection inlet fluid domain of a preset length needs to be constructed in front of the inlet section of the initial multi-stage axial compressor model.

5. The method according to claim 4, characterized in that, The process of meshing the fluid domain includes: Local mesh control is performed on the surface mesh size of each blade surface in the initial multi-stage axial compressor model to ensure that the surface mesh size of each blade surface is within a preset error range. The surface mesh size of the fluid domain at the particle injection inlet is locally controlled to ensure that the surface mesh size of the particle injection inlet surface is within a preset error range.

6. The method according to claim 5, characterized in that, When performing mesh generation of the fluid domain, no boundary layer mesh is generated for the fluid domain in the particle injection inlet section.

7. The method according to claim 6, characterized in that, When numerically solving the fluid domain, the gas is considered as a continuous phase and the particulate matter as a discrete phase. The solution for the continuous phase spatial flow field is obtained using the Euler method, and the solution for the discrete particulate matter is obtained using the Lagrange method to solve for particle trajectories.

8. The method according to claim 7, characterized in that, The method further includes: After obtaining the continuous phase space flow field solution in the multi-stage axial compressor blade passage each time, the accelerated deposition method is used to solve for the discrete phase particles.

9. The method according to claim 8, characterized in that, When the target simulation runtime is divided into N sub-simulation runtimes, the target simulation runtime is evenly distributed to obtain N sub-simulation runtimes.

10. The method according to claim 9, characterized in that, When analyzing the impact of blade fouling on the operating performance of a multi-stage axial compressor, the compressor's total isentropic efficiency, total pressure ratio, total temperature ratio, and mass flow rate are analyzed.

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